The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Quantum physics has a reputation for needing exotic hardware, from liquid-helium-cooled qubits to sprawling AI clusters, just to crunch through basic simulations. Now a new “physics shortcut” is ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

Quantum computing made significant strides in 2024, but it’s yet to demonstrate a practical advantage over classical digital computers, according to a recent trends report released by Forrester ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

Understanding The FASQ Vision Defining Fault-Tolerant Application-Scale Quantum So, what exactly is this "FASQ" thing we keep ...

In the presentation below, Seth Juarez of DevExpress discusses architecting predictive algorithms for machine learning. Machine learning is one of the most important tools in a Data Scientist’s ...

QTUM is a thematic ETF designed to provide exposure to companies involved in quantum computing and machine learning and uses ...